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-trained tool on other image sensors and at different mountain sites presents difficulties. Specifically, generalizing a model trained on a specific site to other sites with different environmental
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. The candidate will need to master sensor technologies, embedded systems, and communication protocols, while integrating real-time data into cloud platforms to develop reliable, secure, and scalable solutions
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of these reusable packaging using IoT sensors and deep learning techniques embedded in the sensors. During the preliminary work, neural network models were developed to perform simple tasks using accelerometer data
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. The successful candidate will be joining the Atomic Quantum Optics group led by Prof. Dr. Morgan Mitchell. The group has several active research topics focused on hot-vapor quantum sensors, including
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for autonomous vehicle control and teleoperation applications. Expertise in the areas of vehicle dynamics, vehicle control, localization, computer vision, sensor fusion and estimation algorithms is desired
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with Danish and international industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as
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industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as postdoc requires academic
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to implement dynamic force control to achieve faster and more tests. The main part of the works of this post-doc position will thus consist in developing a sensorized (instrumented) tip that will
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acceleration. While optical sensors have great advantages, they are challenged by high cost and the difficulty to distinguish various physical quantities. We address these challenges by developing broadband
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with sensor system integration • Familiarity with experimental data analysis and custom device fabrication for materials characterization. • Ability to work effectively in interdisciplinary